Apply zero trust by treating each simulation dataset, application, service, and computing environment as a resource that needs its own access decision. Inventory the data and the systems that use it; identify the people and non-human identities that request access; grant only the operations each task requires; and enforce policy at the application and resource. NIST provides general zero-trust guidance for these practices, but does not prescribe a supply-chain-simulation-specific data classification or architecture.
What zero trust means for simulation workflows
Zero trust does not treat a connection to the internal network, a familiar device, or a previous approval as sufficient reason to trust a request. NIST SP 800-207 (2020) describes an approach that protects resources directly and evaluates access to them. For simulation work, resources include more than the final model or report: they may include source data, configuration files, intermediate results, databases, object stores, compute jobs, APIs, and the services that transform or transfer data.
Authorization should be specific to the resource and requested operation. Permission to read an input dataset should not automatically grant permission to change or delete it, access a separate output, or administer the service that runs the model. NIST’s least-privilege guidance calls for granting only the minimum privileges—such as read, write, or delete—needed for the task.
Include applications and services in the access model, not just employees. A scheduled pipeline, model runner, or data-transfer service can request access just as a person can. NIST SP 800-207A (2023) describes cloud-native policies based on application and service identities as well as user identities and network parameters.
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Apply the controls in five steps
1. Inventory resources and data flows
Map what the simulation workflow uses and produces, and how data moves between its parts. Record an owner or accountable team and the consumers for each resource. Keep the data resource distinct from the network segment carrying it: knowing which subnet hosts a database does not establish who should be able to read its contents.
- Inputs, such as supplier, logistics, or inventory data used by a model.
- Model and configuration files, including versions used for a run.
- Intermediate and final datasets, reports, and exported results.
- Databases, object stores, compute jobs, APIs, and the applications or services that access them.
NIST’s general zero-trust model treats data sources and computing services as resources. Separately, its critical-software security measures call for establishing and maintaining a data inventory. Applying that inventory guidance to simulation datasets is an implementation choice, not a simulation-specific NIST requirement.
2. Identify requesters and define allowed actions
For each workflow, list the human users, devices, applications, and services that request access. Then specify what each identity needs to do on each resource. A researcher might need to read an approved input and write results to a designated output; a pipeline service might need to read inputs and write intermediate files. Treat these as examples to adapt to the real workflow, not as standard role assignments.
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Give applications and services their own identities and policies rather than allowing them to inherit a broad human account or network-level permission. Keep permissions tied to the specific task: where a process only needs to read a dataset, do not grant write or delete access by default.
3. Make each access decision resource- and request-specific
Authenticate and authorize before access, using the requested resource and operation in the decision. Do not treat an approved session as blanket permission to every dataset or service. A successful request to retrieve a model input does not, by itself, authorize a request to modify that input or retrieve a different simulation output.
NIST SP 800-207 describes ongoing evaluation and granular decisions as zero-trust principles. In implementation, balance those checks with availability: policy enforcement should not create authentication delays that make a required workflow unusable.
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4. Enforce policy where applications and resources are accessed
For cloud-native, hybrid, or multi-cloud simulation services, consider enforcement points such as API gateways and sidecar proxies, supported by application identity infrastructure. NIST SP 800-207A describes these components as ways to apply granular, identity-based application policies across on-premises and cloud deployments. It presents architectural options, not a requirement to adopt a particular vendor or product.
Network controls can still contribute to defense, but they should not substitute for identity- and resource-level decisions. NIST SP 800-207A characterizes the shift as moving from controls based on segmentation and network parameters toward identity-based policies. The practical aim is for a request to be evaluated according to who or what is asking, what it wants to do, and which resource it wants to use—even when service locations change.
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Review access requests and resource use, and reassess permissions when an identity, service, dataset, or workflow changes. Check that the controls still support required operations and availability. The cited NIST guidance does not establish a review cadence or simulation-specific monitoring metrics; set those based on your organization’s workflow, risk, and operational requirements.
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Turn the inventory into a permission plan
Use a resource-by-resource plan to make policy gaps visible. The entries below illustrate questions to answer; they are not prescribed permissions or a NIST classification scheme.
| Resource | Requesters to consider | Actions to decide |
|---|---|---|
| Simulation input dataset | Analysts, model-running services, data-ingestion services | Who may read, update, or delete the source data? |
| Model and configuration files | Model owners, approved operators, execution services | Who may read, change, publish, or run each version? |
| Intermediate results or output store | Pipeline services, analysts, designated downstream applications | Who may write results, read them, or remove them? |
| API, database, or compute service | People and applications that call or administer it | Which requests are permitted, and which identities may administer the service? |
For each row, record the accountable owner, the identity making the request, the resource, the action, and the policy enforcement point. This makes it easier to spot permissions that are broader than the task, as well as workflow dependencies that would be disrupted by a proposed restriction.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Choose an implementation approach against the workflow
NIST’s zero-trust implementation guide names enhanced identity governance, identity/credential/access management, microsegmentation, secure access service edge (SASE), and software-defined perimeter among implementation approaches. These categories address different parts of an access architecture; the sources do not compare products or recommend one approach for simulation workloads.
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- Identity coverage: Can the approach govern both user and service identities?
- Permission granularity: Can policy distinguish resources and actions such as read, write, and delete?
- Deployment coverage: Can enforcement work across the on-premises and cloud environments the workflow actually uses?
- Integration: Does it fit the existing APIs, applications, and simulation services?
- Operational effect: What are the implications for availability, latency, usability, and the effort required to operate the controls?
Evaluate the approaches against your inventory and workflow requirements rather than selecting one from its label alone. A network-focused control, for example, should not be assumed to provide the same application-identity and data-action decisions as an application-level policy.
Set the organization-specific policy deliberately
The cited NIST sources do not define which supply-chain simulation inputs or outputs are sensitive, which outside parties or services should receive them, or a universal mapping from sensitivity to controls. Your organization must decide those points from its data, use cases, obligations, and operating needs. For each workflow, ask which inputs and outputs need protection, which identities genuinely need access, and what minimum actions let the work proceed.
Document those decisions alongside the inventory and revisit them when suppliers, models, integrations, or deployment environments change. That keeps the policy tied to the resources and tasks it is meant to protect rather than to assumptions about a trusted network location.
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